Senior Director, AI and Machine Learning – Evinova

Join to apply for the Senior Director, AI and Machine Learning – Evinova role at Evinova.

On average, it takes more than 10 years to develop a drug and costs more than $1.3b. Over 70% of drug R&D cost is spent on clinical development and the success rate from phase I to approval is only around 10%. At Evinova, a health tech business as part of the AstraZeneca Group, we aim to halve the cost and cycle time of clinical trials by using state-of-the-art AI and machine learning.

If you are a solid coder with hands-on experience developing AI agentic solutions, a good understanding of modern deep learning, strong AWS skills, and a voracious learner, you could be a great fit for our team. Background in biostatistics and causal inference will be a strong add-on. Talent with ambition to grow into a role will be a key differentiator. Glass ceiling smashers are especially welcome.

We are looking for a Senior Director of AI and Machine Learning to lead our AI and ML development. This role is a technical expert driving hands-on development from prototyping to production-ready systems. The role will focus on solving complex clinical development challenges using AI and ML, including AI agent design, communication architectures for agents, and automated techniques for designing and evaluating agentic systems, as well as traditional deep learning model development and deployment (including causal machine learning). The role will interact with product, design, engineering, MLOps, domain experts, and partners.

This role is expected to hire and nurture a high-performing team. In-person work is required at a minimum of three days per week.

About The Role

This is a hands-on role with management responsibility; expect 50% time spent coding.

You Will

• Lead the design, development, and deployment of sophisticated agentic AI applications tailored to life sciences and health tech challenges.
• Develop automated techniques for designing and evaluating agentic systems.
• Ideate, develop, and evaluate tools for agents (e.g., search, memory, context compression, communication architectures).
• Design specialized agent/LLM observability pipelines for prototypes and production systems.
• Develop bespoke deep learning models from design, training, testing to deployment.
• Apply causal machine learning for decision making.
• Hire, mentor and develop an AI team, fostering a culture of innovation and continuous learning with best ML and software engineering practices.
• Lead a portfolio of high-impact AI projects.
• Drive technical and project-level architecture decisions, guiding multi-functional teams through AI lifecycles.
• Deliver production-ready code.
• Collaborate in a multidisciplinary environment to align AI initiatives with business objectives and drive digital transformation.
• Represent the company's AI expertise at conferences, publications, and industry events.

Required Skills/Experience

• Ph.D. or equivalent experience in a relevant field (e.g., mathematics, computer science, data science).
• 10+ years of proven experience in applied machine learning, with a strong focus on deep learning, NLP, and generative AI.
• Proven track record of developing creative and novel AI solutions with significant business impact.
• Extensive experience exploring and testing large language model behavior, prompting, and building products with language models.
• Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex).
• Deep understanding of agentic AI concepts and frameworks (e.g., agentic design patterns, multi-agent systems, reinforcement learning) and their applications in healthcare.
• Experience training (fine-tuning) large language models; hands-on experience with DeepSpeed.
• Extensive experience with AWS services (e.g., SageMaker, Bedrock, MSK, EKS, OpenSearch).
• Proven track record of shipping production-level code with best software engineering practices.
• Experience with containerization, CI/CD, and full-stack development.
• Excellent verbal and written communication skills with experience presenting to executives and partners.
• Demonstrated ability to lead and inspire multi-functional teams.
• Experience with TypeScript and AWS CDK.
• Demonstrated technical leadership experience, including successful delivery of large-scale AI projects.
• Experience designing and implementing novel AI architectures or algorithms in real-world products.

Desirable Skills/Experience

• Experience with low-level languages for high-performance ML code (C/C++, Rust, CUDA, etc.).
• Contributions to open-source AI projects or proprietary AI frameworks.
• Expertise in reinforcement learning, few-shot learning, meta-learning, and causal AI.
• Experience in Biostatistics.

Knowledge of drug development or prior experience in the pharmaceutical industry is nice to have but not required.

Why Evinova?

Evinova draws on AstraZeneca’s experience in developing novel therapeutics, informed by insights from thousands of patients and clinical researchers. We aim to accelerate the delivery of life-changing medicines, improve clinical trial design and patient experiences, and think holistically about patient care before, during, and after treatment. We seek solutions that work across the sector, simplify workloads, and benefit patients broadly. By bringing digital and AI solutions to the wider healthcare community, we can help build unified approaches to development and deployment of digital technologies. Evinova represents a unique opportunity to deliver meaningful outcomes with digital and AI for the wider healthcare community.

Interested? Come and join our journey.

What’s next?

Are you imagining yourself joining our team? We can’t wait to hear from you.

Where can I find out more?

Our social media: Follow Evinova on LinkedIn (LinkedIn link omitted in this refined version).

Learn more about Evinova at evinova.com

Date Posted: 02-Sep-2025

Closing Date: 21-Sep-2025

Our mission is to build an inclusive and equitable environment. We welcome applications from all qualified candidates and offer reasonable adjustments/accommodations as needed during the process.